Resumo: O recente desenvolvimento de painéis de “single nucleotide polymorphisms” (SNPs) distribuídos ao longo do genoma possibilitou a realização de diversos trabalhos com diferentes espécies. O processo seletivo promove o aumento ou a diminuição da frequência alélica (ou gênica) em loci específicos do genoma, além de promover o arrasto dos alelos próximos no cromossomo. Desta forma, são formadas regiões do genoma com o aumento na frequência de determinados alelos na população, o que caracteriza a assinatura de seleção. A detecção destas assinaturas é importante para a caracterização dos recursos genéticos, bem como a identificação de genes ou regiões envolvidos no controle e na expressão de características de importância produtiva e econômica. Os ovinos são uma importante espécie para estes estudos, uma vez que encontram-se amplamente dispersos em diferentes ambientes e apresentam grande diversidade fenotípica. Devido à grande quantidade de dados gerados nas análises genômicas, são necessários métodos estatísticos e programas específicos para a detecção de assinaturas de seleção. Assim, os objetivos deste artigo de revisão são apresentar os principais métodos estatísticos e os programas atualmente utilizados para análise de dados genômicos e a detecção de assinaturas de seleção; descrever os resultados dos recentes trabalhos publicados sobre assinaturas de seleção em ovinos; e discutir alguns desafios e oportunidades nesta área de pesquisa.

Abstract: The recent development of genome-wide single nucleotide polymorphism (SNP) arrays made it possible to carry out several studies with different species. The selection process can increase or reduce allelic (or genic) frequencies at specific loci in the genome, besides dragging neighboring alleles in the chromosome. This way, genomic regions with increased frequencies of specific alleles are formed, caracterizing selection signatures or selective sweeps. The detection of these signatures is important to characterize genetic resources, as well as to identify genes or regions involved in the control and expression of important production and economic traits. Sheep are an important species for theses studies as they are dispersed worldwide and have great phenotypic diversity. Due to the large amounts of genomic data generated, specific statistical methods and softwares are necessary for the detection of selection signatures. Therefore, the objectives of this review are to address the main statistical methods and softwares currently used for the analysis of genomic data and the identification of selection signatures; to describe the results of recent works published on selection signatures in sheep; and to discuss some challenges and opportunities in this research field.

Abstract The first horses were brought to Brazil by the colonizers after 1534. Over the centuries, these animals evolved and adapted to local environmental conditions usually unsuitable for exotic breeds, thereby originating locally adapted Brazilian breeds. The present work represents the first description of maternal genetic diversity in these horse breeds based on D-loop sequences. A D-Loop HSV-I fragment of 252 bp, from 141 horses belonging to ten Brazilian breeds / genetic groups (locally adapted and specialized breeds) were analysed. Thirty-five different haplotypes belonging to 18 haplogroups were identified with 33 polymorphic sites. Haplotype diversity (varying from 0.20 to 0.96) and nucleotide diversity (varying from 0.0039 to 0.0239) was lower for locally adapted than for specialized breeds, with the same pattern observed for FST values. Haplogroups identified in Brazilian breeds are in agreement with previous findings in South American samples. The low variability observed mainly in locally adapted breeds, indicates that, to ensure conservation of these breeds, careful reproductive management is needed. Additional genetic characterization studies are required to support accurate decision-making.

This study estimated the genetic diversity and structure of 12 genetic groups (GG) of locally adapted and specialized pigs in the state of Pernambuco using 22 microsatellite markers. Nine locally adapted breeds (Baé, Caruncho, Canastra, Canastrão, Mamelado, Moura, Nilo, Piau and UDB (Undefined Breed)) and 3 specialized breeds (Duroc, Landrace and Large White), totaling 190 animals, were analyzed. The Analysis of Molecular Variance (AMOVA) showed that 3.2% of the total variation was due to differences between genetic groups, and 3.6% to differences between local and commercial pigs. One hundred and ninety eight alleles were identified and apart from the Large White breed, all GG presented Hardy-Weinberg Equilibrium deviations for some loci. The total and effective allele means were lower for Duroc (3.65 and 3.01) and higher for UDB (8.89 and 4.53) and Canastra (8.61 and 4.58). Using Nei's standard genetic distance and the UPGMA method, it was possible to observe that the Landrace breed was grouped with the local genetic groups Canastra, Moura, Canastrão, Baé and Caruncho. Due to the complex admixture pattern, the genetic variability of the 12 genetic groups can be analyzed by distributing the individuals into two populations as demonstrated by a Bayesian analysis, corroborating the results from AMOVA, which revealed a low level of genetic differentiation between the inferred populations.